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Multi-Sensor Data Fusion

December 09, 2019, to December 13, 2019
Continuing Education Center

Louis Giokas

Louis Giokas started out in the aerospace business holding positions in development and management. At General Electric Aerospace (now part of Lockheed Martin) he held positions of software engineer... More

The use of multiple, heterogeneous sensors is often necessary in the case of robot control, autonomous vehicles and military aviation.  Different skills are required, including electrical engineering, computer science and statistics.  These systems can be complex and include many control theory concepts.  In this class series, we will look at the sensor fusion problem, discuss the available algorithms, and examine the types of sensors available using examples as illustration.

December 12 – Day 4 – Sensor Fusion

In this class, we pull together the lessons learned in the previous sessions to come up with a general approach to the problem. We will demonstrate how systems can be developed and discuss some of the tools that will prove useful. This includes frameworks that can be applied to multiple problems.
December 12, 2019 - 2:00pm EST

December 11 – Day 3 – Sensor Types

Understanding the types of sensors involved is critical. Each type of sensor contains different information and covers a different spatial range. By layering sensors in an intelligent way, we can develop the picture required for the task at hand.
December 11, 2019 - 2:00pm EST

December 10 – Day 2 – Algorithms

Many types of algorithms can be used in multi-sensor data fusion. Many are statistical, but not all. In this class, we will discuss the types of algorithms available.
December 10, 2019 - 2:00pm EST
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